Optimization of real-world supply routes by nature-inspired metaheuristics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10250417" target="_blank" >RIV/61989100:27240/22:10250417 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9870405" target="_blank" >https://ieeexplore.ieee.org/document/9870405</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC55065.2022.9870405" target="_blank" >10.1109/CEC55065.2022.9870405</a>
Alternative languages
Result language
angličtina
Original language name
Optimization of real-world supply routes by nature-inspired metaheuristics
Original language description
The traveling salesman problem (TSP) is an iconic permutation problem with a number of applications in planning, scheduling, and logistics. It has also attracted much attention as a benchmarking problem frequently used to assess the properties of a variety of nature-inspired optimization methods. However, the standard libraries of TSP instances, such as the TSPLIB, are often decades old and might not reflect the requirements of modern real-world applications very well. In this work, we introduce several novel TSP instances representing real-world locations of pharmacies in several major cities of the Czech Republic. We look for the optimum routes between the pharmacies by selected nature-inspired algorithms and compare the results obtained on the real-world instances with their results on standard TSPLIB instances. (C) 2022 IEEE.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
<a href="/en/project/LTAIN19176" target="_blank" >LTAIN19176: Metaheuristics Framework for Multi-objective Combinatorial Optimization Problems (META MO-COP)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
ISBN
978-1-66546-708-7
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
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Publisher name
IEEE
Place of publication
Piscataway
Event location
Padova
Event date
Jul 18, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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